Volume 4, Issue 1

Volume 4, Issue 1

Research Article
Open Access
Development of an automated cytological smear staining device for rapid on-site evaluation
Guangyan Wang
Guangyan Wang
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Kai Yang
Kai Yang
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Chunhua Zhou
Chunhua Zhou
Department of Gastroenterology, Ruijin Hospital, Shanghai 200025, China.
,
Duowu Zou
Duowu Zou
Department of Gastroenterology, Ruijin Hospital, Shanghai 200025, China.
,
Shiju Yan
Shiju Yan
yanshiju@usst.edu.cn
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Article Preview PDF CITE Article Preview

Objective: To develop an automated staining device addressing the issues of cumbersome operation, low efficiency, and cluttered workspace associated with current clinical rapid on-site evaluation using Diff-Quik staining for aspiration specimen cytological smears. Methods: The device integrates a microcontroller to control motors, peristaltic pumps, solenoid valves, and fans, enabling the automatic transfer of cytological slides, delivery of staining and rinsing solutions, and forced-air drying. Results: Preliminary test results indicated that the developed device successfully performs four key steps, including Diff-Quik A and B staining, rinsing, and drying, achieving automatic staining of cytological smears. Conclusion: The developed device features a compact footprint and has no pollution to the operating environment, offering a practical solution for automated, efficient, and convenient slide staining during rapid on-site evaluation procedures.

Review Article
Open Access
Review of key technologies in ankle rehabilitation robots
Jiajia Zha
Jiajia Zha
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Qingyun Meng
Qingyun Meng
mengqy@sumhs.edu.cn
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Hongtao Shen
Hongtao Shen
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Mingxia Wei
Mingxia Wei
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Article Preview PDF CITE Article Preview

Ankle rehabilitation robots represent an important branch of rehabilitation robotics, offering significant potential to improve the quality of life for patients with ankle dysfunction caused by stroke, sports injuries, and other conditions. This review first outlines the anatomy and range of motion of the ankle joint, compares conventional rehabilitation approaches with robot-assisted therapy, and highlights the clinical significance of ankle rehabilitation robots. It then systematically examines current research progress from two core perspectives: mechanical structure design and control strategies. In mechanical design, the performance characteristics of series versus parallel mechanisms are compared, the advantages and limitations of actuation methods such as electric motors and pneumatic artificial muscles are analyzed, and the application contexts of platform-based and wearable robots are discussed. In control strategies, the discussion covers motion control and human-robot interaction, beginning with fundamental position, velocity, and trajectory tracking control, and extending to intention-level and cognitive interaction. Finally, based on current research and clinical needs, future ankle rehabilitation robots are expected to evolve toward greater flexibility, intelligence, and universality, providing a theoretical foundation for future studies.

Research Article
Open Access
Design and analysis of a tissue retraction manipulator for neuroendoscopic surgery
Yu Liu
Yu Liu
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200082, China.
,
Gengqiang Shi
Gengqiang Shi
gengersgq@163.com
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200082, China.
Article Preview PDF CITE Article Preview
This paper presents the design and analysis of a compact, cable-driven manipulator specifically for tissue retraction during neuroendoscopic surgery. The manipulator features an underactuated mechanism with a three-joint serial configuration, enabling stable motion within a single plane. Its compact design facilitates seamless integration into standard neuroendoscopic working channels, thereby optimizing spatial efficiency. The kinematic model was established using the Denavit-Hartenberg parameter method, with both forward and inverse kinematics systematically derived. Furthermore, a statics model was developed based on the Lagrangian formulation. Workspace analysis and trajectory planning were performed using Monte Carlo simulations in MATLAB. The simulation results indicate that the manipulator exhibits a feasible crescent-shaped workspace (X∈[10, 50.9] mm, Y∈[5.3, 44.9] mm). The motion trajectories of all joints were observed to be continuous and smooth, without any abrupt changes. Subsequent validation through ADAMS simulations confirmed the smooth variation of joint torques. This study provides a theoretical foundation and offers practical insights for the development and precise control of specialized instruments for neuroendoscopic surgery.
Research Article
Open Access
Heart sound classification based on the fusion of dynamic features and images of mel-frequency cepstral coefficients
Shoucheng Chen
Shoucheng Chen
School of Biomedical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Rongguo Yan
Rongguo Yan
yanrongguo@usst.edu.cn
School of Biomedical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Ke Wang
Ke Wang
School of Biomedical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Wenjing Du
Wenjing Du
School of Biomedical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Article Preview PDF CITE Article Preview
Heart sound analysis plays a key role in the early screening and auxiliary diagnosis of cardiovascular diseases. However, conventional auscultation largely depends on physicians’ personal experience, which often leads to subjective and inconsistent evaluations. To overcome these limitations, this paper presents an intelligent heart sound classification framework that integrates dynamic mel-frequency cepstral coefficient (MFCC) features with dynamic MFCC-based images. In this work, the static MFCCs together with their first- and second-order derivatives are extracted to describe both the spectral and temporal behaviors of heart sounds. A multi-branch fusion model is designed to enhance feature interaction among the dynamic MFCC features via cross-branch attention. Meanwhile, a CA-ResNet18 network incorporating a coordinate attention mechanism is employed to learn spatio-temporal representations from the dynamic MFCC images. The high-level features produced by both models are then concatenated and classified using a support vector machine. Experimental validation on the PhysioNet Challenge 2016 dataset demonstrates that the proposed method achieves 96.82% accuracy, 97.51% sensitivity, and 96.19% specificity. Comparative studies with recent state-of-the-art methods confirm that the proposed integration of dynamic feature fusion and hybrid deep learning–machine learning framework significantly enhances the robustness and classification performance in intelligent heart sound analysis.
Review Article
Open Access
Research progress on hemostatic techniques for combat trauma
Xinying Shi
Xinying Shi
Shanghai Institute for Minimally Invasive Therapy, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Yuan Yao
Yuan Yao
Shanghai Songyu Medical Devices Co., Ltd., Shanghai 200050, China.
,
Haipo Cui
Haipo Cui
h_b_cui@163.com
Shanghai Institute for Minimally Invasive Therapy, University of Shanghai for Science and Technology, Shanghai 200093, China.
Article Preview PDF CITE Article Preview

Combat trauma hemostasis techniques are crucial for modern military medicine in addressing the challenges posed by high-energy destructive weapons. As reported, the incidence of vascular injuries during the Vietnam War was approximately 2%, while that during the Iraq War ranged from 4.4% to 8.2%. Meanwhile, massive hemorrhage caused by various types of vascular injuries is the primary factor leading to acute death among potentially survivable casualties during wartime. This paper provides a detailed exploration of the research progress in combat trauma hemostasis, with a focus on analyzing vascular injuries and uncontrolled bleeding caused by high-energy destructive weapons in modern warfare. Starting from the pathophysiological characteristics of combat trauma, it introduces the four-level priority treatment system established by North Atlantic Treaty Organization and Committee on Tactical Combat Casualty Care, and emphasizes the importance of the “Golden 1-Hour” principle in improving casualty survival rates. The physiological mechanisms of blood coagulation are outlined, followed by an in-depth analysis of both traditional and novel hemostatic techniques, including tourniquets, hemostatic dressings, and auxiliary hemostatic materials. Finally, the challenges faced by combat trauma hemostasis technologies are discussed, along with future development directions.

Review Article
Open Access
AI-assisted diagnosis of myocardial hypertrophy based on cardiac MRI: A systemic review
Shimin Zhou
Shimin Zhou
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Xudong Guo
Xudong Guo
guoxd@usst.edu.cn
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200093, China.
,
Yunli Shen
Yunli Shen
State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200093, China.
,
Qinfen Jiang
Qinfen Jiang
State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200093, China.
,
Xin Gong
Xin Gong
State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200093, China.
,
Jie Ding
Jie Ding
State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200093, China.
,
Yihong Yang
Yihong Yang
Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.
,
Guojie Xu
Guojie Xu
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Jican Wen
Jican Wen
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Jingyang Niu
Jingyang Niu
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Article Preview PDF CITE Article Preview
Cardiac hypertrophy represents a complex pathological condition characterized by ventricular wall thickening, with diverse etiologies and substantial challenges in clinical differential diagnosis. In recent years, rapid advances in artificial intelligence (AI) techniques for CMR image analysis have provided novel technical approaches for the precise diagnosis of cardiac hypertrophy. This paper systematically reviews the research progress of CMR-based AI technologies in the diagnosis of cardiac hypertrophy, including AI diagnostic methods based on Cine-MRI sequences, T1/T2 Mapping sequences, late gadolinium enhancement (LGE) sequences, and multi-sequence fusion strategies. The review further explores the technological evolution from traditional machine learning to deep learning and their applications in differentiating normal from hypertrophic hearts, as well as in the fine classification of cardiac hypertrophy with different etiologies. Furthermore, this paper elucidates the application value of natural language processing (NLP)-based MRI report automatic parsing technology in large-scale case screening and discusses the existing challenges and potential future directions of AI in this field.
Letter to the Editor
Open Access
Slim exquisite easy-exposing video laryngoscope: A novel video laryngoscope
Chenglong Zhu
Chenglong Zhu
School of Anesthesiology, Naval Medical University, Shanghai 200433, China.
,
Zui Zou
Zui Zou
zouzui@smmu.edu.cn
School of Anesthesiology, Naval Medical University, Shanghai 200433, China.
PDF CITE
Research Article
Open Access
A metallic foreign object detection algorithm in pharmaceuticals based on phase rotation and smoothed pseudo-Wigner-Ville distribution
Lin Jiang
Lin Jiang
Department of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Piding Li
Piding Li
lipiding_usst@qq.com
Department of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Article Preview PDF CITE Article Preview
Currently, the pharmaceutical manufacturing industry faces problems such as low accuracy in detecting metal foreign objects due to product effects. To address this issue, this paper proposes a metal detection algorithm based on phase rotation and time-frequency analysis. Phase rotation suppresses product effect interference, and smoothed pseudo-Wigner-Ville distribution (SPWVD) is used to acquire time-frequency images, identifying significant differences representing metal foreign objects and achieving metal detection under strong product effect interference. To ensure computational efficiency meets industrial real-time requirements, an embedded software system with a dual-core CPU and CLA working in tandem is employed, improving algorithm efficiency through hardware improvements. Test results show that the system achieves a detection accuracy exceeding 98% for 0.8 mm ferromagnetic metals and 1.2 mm non-ferromagnetic metals, with a single detection cycle completed within 10 ms.
Progress in Medical Devices
ISSN: 2957-5478
ZENTIME PUBLISHING CORPORATION LIMITED